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Simple stochastic games are turn-based 2.5-player zero-sum graph games with a reachability objective. The problem is to compute the winning probability as well as the optimal strategies of both players. In this paper, we compare the three…

Computer Science and Game Theory · Computer Science 2020-09-24 Jan Křetínský , Emanuel Ramneantu , Alexander Slivinskiy , Maximilian Weininger

Schmidt's game is a powerful tool for studying properties of certain sets which arise in Diophantine approximation theory, number theory, and dynamics. Recently, many new results have been proven using this game. In this paper we address…

Logic · Mathematics 2019-02-20 Lior Fishman , Tue Ly , David S. Simmons

Consider a random vector with finite second moments. If its precision matrix is an M-matrix, then all partial correlations are non-negative. If that random vector is additionally Gaussian, the corresponding Markov random field (GMRF) is…

Statistics Theory · Mathematics 2014-04-29 Martin Slawski , Matthias Hein

We present a deterministic algorithm, solving discounted games with $n$ nodes in $n^{O(1)}\cdot (2 + \sqrt{2})^n$-time. For bipartite discounted games our algorithm runs in $n^{O(1)}\cdot 2^n$-time. Prior to our work no deterministic…

Data Structures and Algorithms · Computer Science 2020-10-27 Alexander Kozachinskiy

Partial-monitoring games constitute a mathematical framework for sequential decision making problems with imperfect feedback: The learner repeatedly chooses an action, opponent responds with an outcome, and then the learner suffers a loss…

Computer Science and Game Theory · Computer Science 2011-10-13 András Antos , Gábor Bartók , Dávid Pál , Csaba Szepesvári

Zero sum games with risk-sensitive cost criterion are considered with underlying dynamics being given by controlled stochastic differential equations. Under the assumption of geometric stability on the dynamics , we completely characterize…

Optimization and Control · Mathematics 2018-01-04 Anup Biswas , Subhamay Saha

A large body of research is currently investigating on the connection between machine learning and game theory. In this work, game theory notions are injected into a preference learning framework. Specifically, a preference learning problem…

Machine Learning · Computer Science 2018-12-20 Mirko Polato , Fabio Aiolli

The celebrated Krusel-Smith growth model is an important example of a Mean Field Game with a common noise. The Mean Field Game is encoded in the master equation, a partial differential equation satisfied by the value of the game which…

Analysis of PDEs · Mathematics 2022-11-16 Yves Achdou , Jean-Michel Lasry , Pierre Louis Lions

We consider zero-sum stochastic games for continuous time Markov decision processes with risk-sensitive average cost criterion. Here the transition and cost rates may be unbounded. We prove the existence of the value of the game and a…

Optimization and Control · Mathematics 2021-09-21 Mrinal K. Ghosh , Subrata Golui , Chandan Pal , Somnath Pradhan

We study zero-sum differential games with state constraints and one-sided information, where the informed player (Player 1) has a categorical payoff type unknown to the uninformed player (Player 2). The goal of Player 1 is to minimize his…

Computer Science and Game Theory · Computer Science 2024-06-05 Mukesh Ghimire , Lei Zhang , Zhe Xu , Yi Ren

We show the convergence of finite state symmetric N-player differential games, where players control their transition rates from state to state, to a limiting dynamics given by a finite state Mean Field Game system made of two coupled…

Probability · Mathematics 2018-12-05 Alekos Cecchin , Guglielmo Pelino

In two-player zero-sum stochastic games, where two competing players make decisions under uncertainty, a pair of optimal strategies is traditionally described by Nash equilibrium and computed under the assumption that the players have…

Optimization and Control · Mathematics 2019-07-30 Yagiz Savas , Mohamadreza Ahmadi , Takashi Tanaka , Ufuk Topcu

The convexification numerical method with the rigorously established global convergence property is constructed for a problem for the Mean Field Games System of the second order. This is the problem of the retrospective analysis of a game…

Numerical Analysis · Mathematics 2023-06-30 Michael V. Klibanov , Jingzhi Li , Zhipeng Yang

We consider the behaviour of $\lambda$-discounted zero-sum games as the discount factor $\lambda$ approaches 0 (that is, the players are more and more patient), in the context of games with stage duration. In stochastic games with stage…

Optimization and Control · Mathematics 2024-07-25 Ivan Novikov

This paper examines multiplayer symmetric constant-sum games with more than two players in a competitive setting, including examples like Mahjong, Poker, and various board and video games. In contrast to two-player zero-sum games,…

Machine Learning · Computer Science 2024-10-04 Jiawei Ge , Yuanhao Wang , Wenzhe Li , Chi Jin

We study the game modification problem, where a benevolent game designer or a malevolent adversary modifies the reward function of a zero-sum Markov game so that a target deterministic or stochastic policy profile becomes the unique Markov…

Computer Science and Game Theory · Computer Science 2024-08-27 Young Wu , Jeremy McMahan , Yiding Chen , Yudong Chen , Xiaojin Zhu , Qiaomin Xie

The numbers game is a one-player game played on a finite simple graph with certain "amplitudes" assigned to its edges and with an initial assignment of real numbers to its nodes. The moves of the game successively transform the numbers at…

Combinatorics · Mathematics 2008-10-31 Robert G. Donnelly , Kimmo Eriksson

Arithmetic functions in Number Theory meet the Sprague-Grundy function from Combinatorial Game Theory. We study a variety of 2-player games induced by standard arithmetic functions, such as Euclidian division, divisors, remainders and…

Number Theory · Mathematics 2021-07-06 Douglas E. Iannucci , Urban Larsson

We consider a randomized algorithm for the unique games problem, using independent multinomial probabilities to assign labels to the vertices of a graph. The expected value of the solution obtained by the algorithm is expressed as a…

Computational Complexity · Computer Science 2015-08-10 Rajeev Kohli , Ramesh Krishnamurti

Optimization under uncertainty is a fundamental problem in learning and decision-making, particularly in multi-agent systems. Previously, Feldman, Kalai, and Tennenholtz [2010] demonstrated the ability to efficiently compete in repeated…

Computer Science and Game Theory · Computer Science 2026-01-29 Daniel Ablin , Alon Cohen